Gut-associated microbes are present and active in the pig nasal cavity

The nasal microbiota is a key contributor to animal health, and characterizing the nasal microbiota composition is an important step towards elucidating the role of its different members. Efforts to characterize the nasal microbiota composition of domestic pigs and other farm animals frequently report the presence of bacteria that are typically found in the gut, including many anaerobes from the Bacteroidales and Clostridiales orders. However, the in vivo role of these gut-microbiota associated taxa is currently unclear. Here, we tackled this issue by examining the prevalence, origin, and activity of these taxa in the nasal microbiota of piglets. First, analysis of the nasal microbiota of farm piglets sampled in this study, as well as various publicly available data sets, revealed that gut-microbiota associated taxa indeed constitute a substantial fraction of the pig nasal microbiota that is highly variable across individual animals. Second, comparison of herd-matched nasal and rectal samples at amplicon sequencing variant (ASV) level showed that these taxa are largely shared in the nasal and rectal microbiota, suggesting a common origin driven presumably by the transfer of fecal matter. Third, surgical sampling of the inner nasal tract showed that gut-microbiota associated taxa are found throughout the nasal cavity, indicating that these taxa do not stem from contaminations introduced during sampling with conventional nasal swabs. Finally, analysis of cDNA from the 16S rRNA gene in these nasal samples indicated that gut-microbiota associated taxa are indeed active in the pig nasal cavity. This study shows that gut-microbiota associated taxa are not only present, but also active, in the nasal cavity of domestic pigs, and paves the way for future efforts to elucidate the function of these taxa within the nasal microbiota.


Characterizing the gut-microbiota associated fraction in the pig nasal microbiota
As the starting point of this study, we aimed to characterize the fraction of gut-microbiota associated taxa found in the nasal microbial communities of piglets.Towards this end, we sampled the nasal cavity and rectum of 24 healthy animals from three different commercial farms located in Spain without a history of respiratory disease outbreaks and used 16S rRNA gene sequencing to determine the microbiota composition (Fig. 1A).We obtained a total number of 9,103 different ASVs (mean of 132,051.44 read counts per sample) after processing the raw reads.To determine the fraction of gut-microbiota associated microorganisms in these samples, we focused on two orders (Bacteroidales/Clostridiales) which constitute the most abundant taxa in the gut microbiota and defined these as "gut-microbiota associated taxa".We found that Bacteroidales and Clostridiales represented a substantial fraction of the pig nasal microbiota in most animals, accounting for 9.43 ± 3.8% and 20 ± 7.7% of the total composition, respectively (mean ± SD across samples) (Fig. 1B, left).As expected, this fraction was higher in the respective rectal swabs (Fig. 1B, right).We also determined this gut-microbiota associated fraction in the pig nasal microbiota in an alternative way by identifying taxa that are prevalent in a reference data set of gut microbiota (obtained from about 300 animals 23 ) and obtained very similar results (supplementary Text 1 and supplementary Fig. 1).Consistent with previous reports 7,11,12 , in the nasal samples, Prevotella and Bacteroides Figure 1.Detection of gut-microbiota associated taxa in nasal and rectal swabs from healthy 2-3 week-old piglets from three farms.(A) Schematic of microbiota sampling and sequencing approaches (created with BioRender.com).(B) Summed relative abundance of Bacteroidales (blue) and Clostridiales (green) taxa in nasal (left) and rectal (right) swabs of 24 individual animals.Summed abundance of other taxa (order level) with > 1% mean relative abundance across samples are shown as "Other" (pink).Orders with < 1% relative abundance are summed in the category "Low abundant".(C) Relative abundances in nasal and rectal samples (mean across 24 individuals) of genera in nasal microbiota with > 0.5% mean relative abundance across animals.Square brackets in taxonomical assignations indicate contested names in the reference Greengenes database used (13.8).
together with Ruminococcaceae and Lachnospiraceae, were the most prevalent taxa within Bacteroidales and Clostridiales, respectively.Reassuringly, other reported nasal colonizers such as Moraxella, Acinetobacter, and Enhydrobacter genera from Pseudomonadales, Lactobacillus and Streptococcus genera from Lactobacillales and Glaesserella from Pasteurellales were also highly abundant in the nasal samples (supplementary Fig. 2).
To assess whether this substantial fraction of gut-microbiota associated taxa is a unique feature of these particular samples, we quantified the fraction of Bacteroidales and Clostridiales in 11 publicly available data sets of pig nasal microbiota samples ( 11,15,20,(24)(25)(26)(27)(28)(29)(30) , see supplementary Table 1).We found that across different countries of origin, pig ages, and sequenced regions, Bacteroidales and Clostridiales represent a substantial (albeit variable between individual animals) fraction of the nasal microbiota (supplementary Fig. 3, supplementary Table 2).Taken together, these results confirm that the pig nasal microbiota has a substantial fraction of commonly gutmicrobiota associated taxa.

Identifying the source of gut-microbiota associated taxa in the pig nasal microbiota
The most probable source of gut-microbiota associated taxa in the pig is the gut microbiota itself, and in support of this hypothesis we found that the most abundant genera belonging to either Bacteroidales or Clostridiales in rectal samples also tended to be highly abundant in matched nasal samples (Fig. 1C).On the other hand, most genera previously reported as nasal colonizers exhibited low abundances in rectal samples (Fig. 1C).However, it is conceivable that although the gut-microbiota associated taxa in these two body sites belong to the same genera, pig nose and gut may nevertheless be inhabited by distinct strains with different niche preferences.
To address this question, we examined the individual ASVs (as a proxy for strain identity 31 ) found in nasal and rectal swabs within each farm.Specifically, for each farm we identified the most abundant Bacteroidales and Clostridiales ASVs in nasal and rectal samples and determined their overlap (the 100 most relatively abundant ASVs in nasal and rectal samples were selected, Fig. 2A, supplementary Table 3).We found that 39%, 14% and 30% of these most abundant ASVs belonging to Bacteroidales, were shared between nose and rectal samples in farms 1, 2 and 3, respectively.In the case of Clostridiales, these proportions were 36%, 9% and 39%.Importantly, we found that the ASVs shared between both body sites were often more highly abundant than the site-specific ones (especially in farms 1 and 3).Notably, only few of these shared ASVs were also found across farms (dark gray circles in Fig. 2A), suggesting that our observations are not simply the result of biases due to high sequence conservation in these taxa.Moreover, we did not observe any biases for certain bacterial families or genera within the body-site specific ASVs.For example, we found ASVs classified as Prevotella, Bacteroides, Veillonella Figure 2. Nasal and rectal overlap of gut-microbiota associated taxa (A) and nasal colonizers (B) most prevalent ASVs per sampled farm.For gut-microbiota associated taxa the 100 most abundant ASVs in nasal and rectal samples were selected.For other nasal colonizers' families (B), the top 20 ASVs were considered.Each dot corresponds to one ASV (mean abundance of 8 animals from each herd).Turquoise: ASV is among the most abundant ASVs in nasal but not rectal swabs.Yellow: ASV is among the most abundant ASVs in rectal but not nasal swabs.Pink: ASV is among the most abundant ASVs in both sites.Dark gray: ASV is among the most abundant ASVs in both sites, and also shared across the three sampled farms.
and Oscillospira among the site-specific ASVs in both nasal and rectal samples (supplementary Table 3), and phylogenetic analysis of these most abundant Bacteroidales and Clostridiales sequences, showed little clustering across body sites and farms (supplementary Fig. 4).In contrast to Bacteroidales and Clostridiales, ASVs belonging to families of known nasal colonizers such as Moraxellaceae, Pasteurellaceae and Weeksellaceae showed a much lower degree of overlap between body sites (Fig. 2B).Among the exceptions we found Lactobacillaceae and Streptococcaceae, whose ASVs still exhibited substantial overlap between the two body sites.Thus, the analysis of nasal and rectal microbiota at ASV level suggests a shared origin of the gut-microbiota associated taxa (presumably environmental e.g. through transfer of fecal matter) found in the pig nasal and rectal microbiota.

Surgical deep sampling of the pig nasal cavity to identify gut-microbiota associated taxa at different depths
The shared gut-microbiota associated taxa in nasal and rectal swabs described above are consistent with the hypothesis that these taxa enter the pig nasal cavity through the transfer of fecal matter driven by the animals' rooting behavior.To further validate that these taxa were indeed resident in the pig nasal cavity and did not stem from contaminations introduced by the sampling through the nostrils, we performed additional in-depth sampling (Fig. 3A).Specifically, we surgically opened the nasal cavity of five animals post-mortem to enable sampling of its (normally inaccessible) deep and middle parts (as detailed in the "Methods" section), avoiding a possible swab contamination from the skin surrounding the nostril openings.Additionally, standard nasal swabs, swabs of the external nasal area, and rectal swabs of each animal were taken for comparison.We observed a gradient in microbial load (highest to lowest, as determined by 16S rRNA gene qPCR) from external to deep internal samples, which was consistent with the number of total reads and abundance of contaminant sequences from negative control samples (supplementary Fig. 5).Moreover, the deep nasal microbiota exhibited lower richness compared to samples from external nose (Chao1 index p < 0.05, supplementary Fig. 6A), and was identified as a distinct community (as determined by beta diversity analysis) compared to the external nares (Jaccard and Bray-Curtis PERMANOVA p < 0.05, supplementary Fig. 6A, supplementary Table 4), when deep nasal samples were compared pairwise with standard and external swab samples.Comparison of the composition at different nasal cavity locations within the same animal revealed that those taxa which were found at all sampling sites www.nature.com/scientificreports/(of which there were only few in any given animal) tended to constitute the bulk of the observed microbiota (supplementary Fig. 7, see supplementary text 2 for detailed compositional analysis).This dominance of few taxa was found both at the genus level, as well as at the level of individual ASVs, suggesting that the nasal microbiota of individual animals is consistently composed of few dominating strains across the whole nasal cavity.Importantly, nasal swabs as well as matched surgical nasal samples showed a variable, but substantial, fraction of gut-microbiota associated taxa (Fig. 3B and supplementary Fig. 6B), many of which were found consistently throughout the nasal cavity in each animal (Fig. 3C).Thus, these findings suggest that gut-microbiota associated taxa do reside in the pig nasal cavity and do not stem from contaminations introduced by the sampling procedure (i.e.sampling through the nostril using swabs) itself.

Assessing the activity of gut-microbiota associated taxa by quantifying the 16S rRNA transcripts
The results described above suggested that gut-microbiota associated taxa are present throughout the whole pig nasal cavity.Next, we wanted to determine whether these taxa (which include many obligate anaerobic species) are also active in the aerobic environment of the pig nose.Towards this end, we quantified 16S rRNA gene transcripts (a proxy for protein synthesis potential and thus indirect measure of cellular activity, [32][33][34] ) in the nasal microbiota samples described above.We found that gut-microbiota associated taxa constituted a similar portion in these RNA derived samples as in the respective DNA samples described above.Specifically, in nasal samples taken from 24 animals across 3 farms, Bacteroidales and Clostridiales orders accounted for a mean 7.1% ± 6.2 and 22.4% ± 14.1, respectively (Fig. 4A and Supplementary Fig. 8A).In the surgical samples taken at different sites in the nasal cavity, Bacteroidales accounted for 10.3% ± 8.8 (Deep), 8.2% ± 10.4 (Middle), 1.6% ± 3.2 (Standard) and 0.1% ± 0.1 (External); and Clostridiales for 3.6% ± 2.8 (Deep), 3.9% ± 3.6 (Middle), 3.2% ± 5.6 (Standard) and 2.9% ± 4.6 (External) (Fig. 4A and Supplementary Fig. 8B).Moreover, we found that gut-microbiota associated taxa had similar RNA to DNA ratios as the ratios for reported nasal colonizers when examined globally (summing across different taxa) in individual animals (Fig. 4B), or when examining different genera (Fig. 4C) and families (supplementary Fig. 9).To identify individual families belonging to gut-microbiota associated taxa that deviate from this general trend, we finally compared their RNA/DNA ratio distributions with those of nasal colonizers in the farm animal samples (supplementary Fig. 10).With some exceptions (e.g.lower RNA/ DNA ratios for Bacteroidales (unclass.)and higher ratios for Clostridiaceae), RNA/DNA ratio distributions were largely not significantly different for most gut-microbiota associated taxa compared to reported nasal colonizers.Taken together, these results suggest that gut-microbiota associated taxa are not only present in the pig nasal environment, but also active.

Discussion
In this study, we aimed to elucidate the role of typically gut-microbiota associated taxa in the nasal cavity of domestic pigs.Specifically, we asked three questions: (1) how prevalent are these taxa in vivo and across different anatomical sites in the nasal cavity?; (2) do these taxa indeed stem from the gut microbiota?; and (3) are these taxa active in the pig nasal cavity?To answer these questions, we used a combination of regular swab and surgical deep sampling of the pig nasal microbiota and inferred its composition/activity by 16S rRNA gene DNA and cDNA sequencing, respectively.These efforts yielded three key findings.First, we found that gut-microbiota associated taxa constitute a substantial fraction of the nasal microbiota both across individual animals, as well as across different sites within the nasal cavity.This finding is in agreement with previous studies, which sampled the pig nasal microbiota, and is also consistent with other studies relying on sampling of the lower respiratory tract of pigs, where Clostridium and Prevotella genera were prevalent 7,13,35 .Thus, our results confirm that gut-microbiota associated taxa are part of the swine nasal respiratory microbiota and are not a sampling artifact.Nevertheless, the sampling of environments that do not have high microbial biomass, including many anatomical sites in the respiratory tract 36,37 , can pose technical challenges such as the false detection of transient environmental microbes 37 .Although we controlled for some potential sources of contamination (sequencing blank controls and getting undisturbed nasal samples) more studies are needed to validate the inhabitants of the pig nasal microbiota.
Second, our analysis of matched nasal and rectal microbiota samples from different farms showed a large overlap between gut-microbiota associated taxa from these two sites at ASV level.This finding suggests a common source of these taxa in both anatomic sites, for example in the form of solid fecal matter that enters the nasal cavity 12,20 , or through the air within a farm.In support of this hypothesis, a recent study found that gutmicrobiota associated taxa are highly abundant in the air of pig farms, as well as in the nasal microbiota of pig farmers (compared to non-exposed individuals) 38,39 , suggesting substantial flow of bacterial material within animal farms.In contrast to gut-microbiota associated taxa, many other dominant taxa in the nasal microbiota, such as Moraxellaceae, Pasteurellaceae, and Weeksellaceae, showed a low degree of overlap between the two body sites, indicating that they may be professional nasal colonizers with reduced ability to colonize other (i.e.anaerobic) niches.Interesting exceptions were the Lactobacillus and Streptococcus genera, which also overlapped substantially at ASV level between these two body sites.Given that both Lactobacillus and Streptococcus are facultative anaerobes, it is tempting to speculate whether these genera may in fact predominantly reside in the gut, but are also able to colonize the nasal cavity (and possibly other sites) if presented with the opportunity.
Third, our quantification of 16S rRNA expression showed that gut-microbiota associated taxa are indeed active in the pig nasal cavity.To our knowledge, this is the first study which quantified pig nasal microbiota activity in vivo, and it suggests that these gut-microbiota associated taxa are not merely inactive transient members in the nasal cavity.Notably, recent metatranscriptomics analyses did report expression of some gut-microbiota associated taxa (e.g.Prevotella) in nasal samples taken from children 40 and adult patients with asthma 41 , suggesting that these taxa may also be active in the human nasal cavity.One caveat is that we quantified 16S rRNA gene transcripts to determine the activity of gut-microbiota associated taxa in the pig nasal microbiota, which is an imperfect measure of cellular activity 32 .Future efforts could examine the activity of these taxa with methods that quantify metabolic activity more directly, for example by using fluorescently-tagged metabolic probes [42][43][44] or metaproteomics 45 .
This study has several limitations.First, we sampled animals at an early age (i.e.pre-weaning stage at 2-3 weeks of age).Our choice was motivated by the fact that pigs at this age are most susceptible to respiratory pathogens, while the nasal microbiota is still rather unstable 11,46 .Nevertheless, our analysis of other published studies did reveal that gut-microbiota associated taxa are also prevalent at later stages in the animals' life 20,25,29 , and future studies may examine to which extent the findings presented herein also hold in adult pigs and other species.
Second, although our comparison of abundant 16S DNA ASVs does indicate a shared origin of gut-microbiota associated taxa in the nasal and gut microbiota, our analysis was restricted to one section of the 16S DNA (variable regions V3-V4).Therefore, strains that share this DNA region, but differ in other parts of their 16S DNA (or other parts of their genome), cannot be distinguished with the approach chosen here.Given that we only identified few ubiquitous ASVs (that is, ASVs conserved across all three tested farms) within these taxa, we argue that our approach has the necessary resolution to detect strain differences.Nevertheless, to further validate that gut-microbiota associated strains are indeed shared by the nasal and gut microbiota, and to identify the species these strains belong to, future studies may use either full-length 16S DNA sequencing, or metagenomics, of matched nasal and gut microbiota samples.
Third, although our surgical samples suggest that gut-microbiota associated taxa are present throughout the pig nasal cavity, the methods used in this study are not able to resolve whether these taxa are located in any specific anatomical niches.Scanning electron microscopy imaging of the upper respiratory tract of piglets has recently suggested the absence of anaerobic crypts 12 , but it is conceivable that there may still be anaerobic substructures e.g.within or under the mucosal layer.Such potential substructures or locations may explain why strictly anaerobic bacterial taxa survive and are active in a basically aerobic environment such as nasal cavity.
To resolve these questions, future efforts may use in vivo imaging methods like these 47,48 to resolve the microstructure of the nasal microbiota in more detail.
Fourth, in this study we analyzed various nasal microbiota samples, but did not specifically address the impact of environmental factors.For example, while we found that gut-microbiota associated taxa are prevalent in the pig nasal microbiota across many studies (see Supplementary Fig. 3), their relative abundance varied widely across these samples.Moreover, the degree of overlap of gut-microbiota associated ASVs between nasal and gut microbiota samples varied between the three different farms (i.e. with farm 2 showing a much lower overlap, an observation for which we currently do not have an explanation).Further epidemiological studies may use www.nature.com/scientificreports/this work as a starting point to assess the impact of environmental factors such as feeding strategies, housing conditions, or sanitation protocols, on the presence of gut-microbiota associated taxa in the nasal microbiota.Finally, while our results do suggest that gut-microbiota associated taxa are indeed active in the pig nasal cavity, we did not examine the in vivo function of these taxa within the pig nasal microbiota.Recent in vivo studies 11,[13][14][15][16][17]49 have shown that the presence of these taxa is associated with disease outcomes and dysbiosis in various farm animals, but also in humans 41 . Fo example, in humans with chronic rhinosinusitis, Prevotella (genus belonging to Bacteroidales) was associated with increased inflammatory severity 50 .Future studies may use the results presented here as a starting point to elucidate the mechanistic underpinnings of these associations.
In conclusion, this study suggests that gut-microbiota associated taxa are indeed present and active in the nasal cavity of domestic pigs.These findings may serve as a starting point for future research aiming at elucidating the in vivo function of these taxa within the nasal microbiota.

Animal experimentation and ethics approval
Animal experimentation was performed following proper veterinary practices, in accordance with European (Directive 2010/63/EU) and Spanish (Real Decreto 53/2013) regulation, and in compliance with the ARRIVE guidelines (https:// arriv eguid elines.org/ about).Sampling in farms was done with the approval of the Ethics Commission in Animal Experimentation of the Generalitat de Catalunya (Protocol number 11213).For the surgical sampling of five animals' different nasal depths, euthanasia was performed following good veterinary practices.According to European (Directive 2010/63/EU of the European Parliament and of the Council of 22 September 2010 on the protection of animals used for scientific purposes) and Spanish (Real Decreto 53/2013) normative, this latter procedure did not require specific approval by an Ethical Committee (Chapter I, Article 3. 1 of 2010/63/EU).

Farm samples
Matched nasal and rectal swabs were taken from 24 healthy 2-3-week-old piglets from three commercial farms from Spain without reported respiratory diseases (termed Farm 1, Farm 2, Farm 3).After sampling, swabs were placed into sterile tubes filled with 1000µL DNA/RNA shield (Zymo Research) and transported to the laboratory under refrigeration.

Surgical samples
Deep surgical samples of the nasal cavity were obtained as follows: five healthy piglets of 2-3 weeks of life were moved to IRTA-CReSA facilities and euthanized by means of an overdose of sodium pentobarbital (Dolethal).Four types of nasal swabs per piglet were taken (labeled standard, external, middle, and deep) as described below.First, a nasal swab from one nostril was taken ("standard" swab, Fig. 3A).Second, an external swab was taken by introducing the swab superficially in the second nostril.Afterwards, deep and middle swabs were taken (at positions outlined in Fig. 3A) from the second nostril after longitudinally cutting and separating the skin of each piglet's head (to prevent contaminations from the skin surface) and subsequent cutting the skull, directly from the nasal turbinate without touching any other part of the piglet nose to avoid contamination and after removing the cartilaginous nasal wall.Additionally, rectal swabs were obtained from the same animals.Sample swabs were collected in sterile plastic tubes filled with 800 µL of DNA/RNA shield (Zymo Research) to ensure the stability and preservation of the genetic material.Negative controls (sterile DNA/RNA shield without a swap) were included in each extraction.Samples were stored at -20 °C until extraction.

DNA/RNA extraction
Metagenomic DNA and RNA were extracted starting from 350 µL of DNA/RNA shield swab sample (previously vortexed) and following a modified protocol of ZymoBIOMICS DNA/RNA Miniprep kit (Zymo Research) in which the lysis was performed only chemically using 700 µL of ZymoBIOMICS DNA/RNA lysis buffer (2 volumes of lysis buffer per 1 volume of sample).The RNA fraction of the samples was treated with 80 µL of DNAse I (included in the kit) at room temperature for 20 min.Elution of both DNA and RNA was done in 50 µL of elution buffer.DNA and RNA concentration was measured using BioDrop DUO (BioDrop Ltd).DNA and RNA were stored at -80 °C until sequencing.

16S rRNA gene sequencing
16S rRNA gene libraries were prepared from the total extracted DNA and cDNA from RNA samples and sequenced at Servei de Genòmica, Universitat Autònoma de Barcelona (Illumina pair-end 2X300 bp, MS-102-2003 MiSeq Re-agent Kit v2, 500 cycle), using Illumina recommended primers for variable regions V3V4 of 16S rRNA gene (fwd 5′TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG CCT ACGGGNGGC WGC AG, rev 5′ GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACA GGA CTACHVGGG TAT CTA ATC C).The size of the amplicons was verified on a Bioanalyzer DNA 1000 chip (Agilent), as expected amplicon length was approximately 460 bp.Finally, the sequences were sorted into samples and used as input for bioinformatic analysis.

Bioinformatic analysis of 16S rRNA sequencing data
The microbiota composition of the samples was analyzed with quantitative insights into microbial ecology (QIIME) 2 software version 2022.2 51 .The detailed pipeline followed from raw reads to obtain tables of abundances at ASV and other taxonomic levels, the diversity analyses and the statistical tests to determine the www.nature.com/scientificreports/differential abundances, can be found at https:// zenodo.org/ record/ 80139 97 (Zenodo ID 8013997).Briefly, the pre-processing of the reads was done separately for each sequencing run.At first, raw demultiplexed reads with quality (fastq) were imported and their quality was evaluated with qiime2 demux plugin.Primers from the variable region V3-V4 were extracted using qiime2 cutadapt plugin 52 Sequences that did not contain primers and thus, were not a sequencing product, were removed from the analysis.DADA2 software package 53 was used under the parameters detailed in the pipeline to quality filter, paired-end merge, remove chimeras and sort reads into ASVs.Contaminant artifactual amplicons from non-prokaryotic origin were identified with qiime2 quality control plugin 54 by aligning with VSEARCH 55 all ASVs against Greengenes database Vs. 13.8 56 clustered with 88% identity (available at https:// docs.qiime2.org/ 2022.2/data-resou rces/).Unmatched sequences were filtered out from the analysis.Additionally, ASVs identified as Archea, Mitochondria or Chloroplast (which also contain 16S rRNA), were also discarded.The alignment of the remaining sequences was performed with MAFFT 57 , and the hypervariable positions were masked 58 with qiime2 alignment plugin.Finally, ASVs found in the negative control of the deep nose dataset were removed from the analysis (21 and 41 for DNA and RNA controls, respectively, Supplementary table 7).The taxonomic classification of the ASVs was performed using a naïve Bayes classifier with scikit-learn Python module for machine learning 59 .In order to increase the classifier accuracy 60 , it was previously trained against prokaryotic 16S rRNA gene V3-V4 region, extracted from Greengenes database (13.8 version) clustered at 99% sequence identity.This qiime2 feature classifier artifact can be found at https:// zenodo.org/ record/ 80139 97 (Zenodo ID 8013997).Square brackets in taxonomical assignations indicate contested names in the reference Greengenes database used (13.8).
In order to normalize uneven sampling depths 61 , the diversity analyses of the samples from the surgical sampling (supplementary text 2) were performed at a normalized depth of 2291, corresponding to the lowest depth sample.The alpha diversity of the samples was estimated with Chao1 62 and Shannon 63 indexes.Significant differences were found with pairwise non-parametric t-tests (999 random permutations) using qiime2 diversity alpha-group-significance plugin 64 .Beta diversity was calculated with Jaccard 65 and Bray-Curtis 66 dissimilarity indexes for the qualitative and quantitative analyses, respectively.Qiime2 core-metrics plugin 67,68 was used to compute principal coordinate (PCoA) analysis.The percentage of explanation of the variables under study was estimated with the Adonis function from the Vegan package, in R software 69 .The significance of beta diversity analyses was calculated by PERMANOVA pairwise test (999 random permutations) using qiime2 diversity betagroup-significance plugin 70 .Differently abundant taxa between groups were found with ANCOM-BC algorithm 71 .For all the stated analyses, the significance threshold p value was set to 0.05.To perform the phylogenetic analyses, the ASVs of interest were multiple aligned with MAFFT 57 , from where the phylogeny was built with the IQtree 72 online tool (available in: http:// iqtree.cibiv.univie.ac.at/) using automatic selection of the substitution model, with 1,000 bootstrap alignments and iterations.Output microbiota data processing and plot generation was performed using R script language version 4.2.2 in RStudio environment version 2022.07.0 73 , using the packages qiime2r 74 , reshape2 75 , ggplot2 76 , tidyverse 77 , and ggtree 78 , as well as MATLAB (version 2021A).

Quantification of total 16S rRNA gene concentration
Total 16S rRNA gene concentrations (as a proxy for microbial load in swabs) were quantified as follows.Briefly, the reaction was prepared in a volume of 20 µL consisting in 2 µL of the template DNA and 18 µL of Femto Bacterial qPCR Premix, which includes a primer mix targeting the 16S rRNA (Femto Bacterial DNA Quantification Kit, Zymo Research).The PCR reaction was performed using a 7500 Fast Real-Time PCR System (ThermoFisher Scientific) at 95 °C for 10 min, 40 cycles of 95 °C for 30 s, 50 °C for 30 s, 72 °C for 1 min, followed by a melting curve and a final extension of 72 °C for 7 min.Each run contained two replicates per sample, a standard curve of 6 points (2-0.00002ng), a negative and a positive extraction control as well as PCR negative controls.Graphpad 8.3 (538) Prism software (Dotmatics, San Diego CA) was used to analyze the data obtained from the 16s rRNA qPCR of DNA extracted from the swabs.

Figure 3 .
Figure 3. Characterization of surgical microbiota samples.(A) Collection of nasal samples at four sites.External and standard nasal sampling; deep and middle nose samples after longitudinal surgical cuts of piglet heads (see "Methods").(B) Summed relative abundance of Bacteroidales (blue) and Clostridiales (green) taxa in the different types of nasal swabs of the 5 individual animals.Summed abundance of orders with > 1% mean relative abundance across samples are shown as "Other" (pink).Taxa with < 1% relative abundance are summed in the category "Low abundant".(C) Most prevalent genera across the nose of the 5 sampled piglets.Genera are ordered from top to bottom by prevalence (present in most samples) and global relative abundance.Gutmicrobiota associated genera are labelled in blue (Bacteroidales) and green (Clostridiales).Numbered column on the right: mean relative abundance across all samples.Sample sites are marked as E(xternal), S(tandard), M(iddle), D(eep).

Figure 4 .
Figure 4. RNA-based quantification of nasal microbiota activity.(A) Summed relative abundance of Bacteroidales (blue) and Clostridiales (green) taxa in the two sets of nasal samples (nasal swabs from 24 farm animals, left; surgical samples from 5 animals, right; see "Methods").Other taxa (order level) with > 1% mean relative abundance are shown as "Other" (pink).Taxa with < 1% relative abundance are summed in the category "Low abundant").(B) Relative abundance in RNA/DNA samples of Bacteroidales (blue), Clostridiales (green), and nasal colonizers (Lactobacillaceae, Moraxellaceae, Pasteurellaceae, Streptococcaceae and [Weeksellaceae], pink).Each dot corresponds to the abundances of the mentioned taxa in one individual animal.Open circles: invasive nasal samples from 5 animals (deep and middle nasal cavity, see Fig. 3).Filled circles: standard nasal swabs from 24 animals across 3 farms.(C) Relative abundance in DNA and RNA samples (as determined by 16S rRNA sequencing of DNA and cDNA, see main text) of the most relatively abundant genera, selected as those > 0.1% mean abundance in DNA or RNA farm samples.Gut-microbiota associated taxa (Bacteroidales and Clostridiales) are labelled in blue and green, respectively.Genera from other orders are shown in pink.Open circles: deep nasal samples obtained surgically from 5 animals (deep and middle nasal cavity, see Fig. 3).Filled circles: standard nasal swabs from 24 animals across 3 farms.Shown are mean values across all samples. https://doi.org/10.1038/s41598-024-58681-9 14:8470 | https://doi.org/10.1038/s41598-024-58681-9